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      <div class="title">prtRegressRvmSequential/prtRegressRvmSequential</div>
      <div class="helptext"><pre><!--helptext -->  prtRegressRvm  Relevance vector machine regression object
 
    This code is based on:
 
        Michael E Tipping, Sparse bayesian learning and the relevance 
        vector machine, The Journal of Machine Learning Research, Vol 1.
 
    Also see <a href="http://en.wikipedia.org/wiki/Relevance_vector_machine">http://en.wikipedia.org/wiki/Relevance_vector_machine</a>
  
    A prtRegressionRvm object inherits the PLOT method from the
    prtRegress object, and the TRAIN, RUN, CROSSVALIDATE and KFOLDS
    methods from the prtAction object.
 
    Example:
    
    dataSet = prtDataGenNoisySinc;           % Load a prtDataRegress
    dataSet.plot;                    % Display data
    reg = <span class="helptopic">prtRegressRvmSequential</span>;   % Create a prtRegressRvm object
    reg = reg.train(dataSet);        % Train the prtRegressRvm object
    reg.plot();                      % Plot the resulting curve
    dataSetOut = reg.run(dataSet);   % Run the regressor on the data
    hold on;
    plot(dataSet.getX,dataSetOut.getX,'c.') % Plot, overlaying the
                                            % fitted points with the 
                                            % curve and original data
    hold off;
    legend('Regression curve','Original Points','Selected Relevant Points','Fitted points',0)</pre></div><!--after help --><!--seeAlso--><div class="footerlinktitle">See also</div><div class="footerlink"> <a href="./../prtRegress.html">prtRegress</a>, <a href="./../prtRegressGp.html">prtRegressGp</a>, <a href="./../prtRegressLslr.html">prtRegressLslr</a>
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